Pandas Profiling Report

Dataset statistics

Number of variables	85
Number of observations	3472
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	7
Duplicate rows (%)	0.2%
Total size in memory	2.3 MiB
Average record size in memory	680.0 B

Variable types

Numeric	6
Categorical	79

Warnings

`secure_doors/windows(drzwi/okna_antywłamaniowe)` has constant value "0.0"	Constant
`intercom/videophone(domofon/wideofon)` has constant value "0.0"	Constant
`monitoring/security(monitoring/ochrona)` has constant value "0.0"	Constant
`closed_area(teren_zamknięty)` has constant value "0.0"	Constant
`garage/parking_space(garaż/miejsce_parkingowe)` has constant value "0.0"	Constant
`only_for_non-smokers(tylko_dla_niepalących)` has constant value "0.0"	Constant
Dataset has 7 (0.2%) duplicate rows	Duplicates
`area` is highly correlated with `room_num` and 1 other fields	High correlation
`room_num` is highly correlated with `area` and 1 other fields	High correlation
`floor` is highly correlated with `total_floor`	High correlation
`total_floor` is highly correlated with `floor`	High correlation
`fridge(lodówka)` is highly correlated with `furniture(meble)` and 2 other fields	High correlation
`furniture(meble)` is highly correlated with `fridge(lodówka)` and 1 other fields	High correlation
`stove(kuchenka)` is highly correlated with `fridge(lodówka)` and 1 other fields	High correlation
`washer(pralka)` is highly correlated with `fridge(lodówka)` and 2 other fields	High correlation
`internet` is highly correlated with `cable TV(telewizja kablowa)`	High correlation
`cable TV(telewizja kablowa)` is highly correlated with `internet`	High correlation
`build_type_Apartment_high_q(apartamentowiec)` is highly correlated with `build_type_Apartment_medium_q(blok)`	High correlation
`build_type_Apartment_medium_q(blok)` is highly correlated with `build_type_Apartment_high_q(apartamentowiec)`	High correlation
`windows_Plastic(plastikowe)` is highly correlated with `windows_Wooden(drewniane)`	High correlation
`windows_Wooden(drewniane)` is highly correlated with `windows_Plastic(plastikowe)`	High correlation
`gross_price` is highly correlated with `area` and 1 other fields	High correlation
`area` is highly correlated with `room_num` and 1 other fields	High correlation
`room_num` is highly correlated with `area` and 1 other fields	High correlation
`floor` is highly correlated with `total_floor`	High correlation
`total_floor` is highly correlated with `floor`	High correlation
`fridge(lodówka)` is highly correlated with `furniture(meble)` and 2 other fields	High correlation
`furniture(meble)` is highly correlated with `fridge(lodówka)` and 1 other fields	High correlation
`stove(kuchenka)` is highly correlated with `fridge(lodówka)` and 1 other fields	High correlation
`washer(pralka)` is highly correlated with `fridge(lodówka)` and 2 other fields	High correlation
`internet` is highly correlated with `cable TV(telewizja kablowa)`	High correlation
`cable TV(telewizja kablowa)` is highly correlated with `internet`	High correlation
`build_type_Apartment_high_q(apartamentowiec)` is highly correlated with `build_type_Apartment_medium_q(blok)`	High correlation
`build_type_Apartment_medium_q(blok)` is highly correlated with `build_type_Apartment_high_q(apartamentowiec)`	High correlation
`windows_Plastic(plastikowe)` is highly correlated with `windows_Wooden(drewniane)`	High correlation
`windows_Wooden(drewniane)` is highly correlated with `windows_Plastic(plastikowe)`	High correlation
`gross_price` is highly correlated with `area` and 1 other fields	High correlation
`area` is highly correlated with `room_num` and 1 other fields	High correlation
`room_num` is highly correlated with `area` and 1 other fields	High correlation
`fridge(lodówka)` is highly correlated with `furniture(meble)` and 2 other fields	High correlation
`furniture(meble)` is highly correlated with `fridge(lodówka)` and 1 other fields	High correlation
`stove(kuchenka)` is highly correlated with `fridge(lodówka)` and 1 other fields	High correlation
`washer(pralka)` is highly correlated with `fridge(lodówka)` and 2 other fields	High correlation
`internet` is highly correlated with `cable TV(telewizja kablowa)`	High correlation
`cable TV(telewizja kablowa)` is highly correlated with `internet`	High correlation
`build_type_Apartment_high_q(apartamentowiec)` is highly correlated with `build_type_Apartment_medium_q(blok)`	High correlation
`build_type_Apartment_medium_q(blok)` is highly correlated with `build_type_Apartment_high_q(apartamentowiec)`	High correlation
`windows_Plastic(plastikowe)` is highly correlated with `windows_Wooden(drewniane)`	High correlation
`windows_Wooden(drewniane)` is highly correlated with `windows_Plastic(plastikowe)`	High correlation
`gross_price` is highly correlated with `area` and 1 other fields	High correlation
`internet` is highly correlated with `telephone(telefon)` and 1 other fields	High correlation
`gross_price` is highly correlated with `area` and 1 other fields	High correlation
`washer(pralka)` is highly correlated with `stove(kuchenka)` and 2 other fields	High correlation
`telephone(telefon)` is highly correlated with `internet` and 1 other fields	High correlation
`build_type_Apartment_high_q(apartamentowiec)` is highly correlated with `build_type_Apartment_medium_q(blok)`	High correlation
`stove(kuchenka)` is highly correlated with `washer(pralka)` and 2 other fields	High correlation
`cable TV(telewizja kablowa)` is highly correlated with `internet` and 1 other fields	High correlation
`heating_Gas(gazowe)` is highly correlated with `heating_Central(miejskie)`	High correlation
`windows_Wooden(drewniane)` is highly correlated with `windows_Plastic(plastikowe)`	High correlation
`floor` is highly correlated with `total_floor`	High correlation
`furniture(meble)` is highly correlated with `washer(pralka)` and 2 other fields	High correlation
`build_type_Apartment_medium_q(blok)` is highly correlated with `build_type_Apartment_high_q(apartamentowiec)` and 1 other fields	High correlation
`area` is highly correlated with `gross_price` and 1 other fields	High correlation
`elevator(winda)` is highly correlated with `total_floor`	High correlation
`build_type_Tenement(kamienica)` is highly correlated with `build_type_Apartment_medium_q(blok)`	High correlation
`windows_Plastic(plastikowe)` is highly correlated with `windows_Wooden(drewniane)`	High correlation
`total_floor` is highly correlated with `floor` and 1 other fields	High correlation
`heating_Central(miejskie)` is highly correlated with `heating_Gas(gazowe)`	High correlation
`room_num` is highly correlated with `gross_price` and 1 other fields	High correlation
`fridge(lodówka)` is highly correlated with `washer(pralka)` and 3 other fields	High correlation
`oven(piekarnik)` is highly correlated with `fridge(lodówka)`	High correlation
`internet` is highly correlated with `closed_area(teren_zamknięty)` and 6 other fields	High correlation
`build_mat_Other(inne)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ mazowieckie` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Żoliborz` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_type_Infill(plomba)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Metro Wilanowska` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Praga-Południe` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_type_Private_house_1_fam(dom wolnostojący)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`washer(pralka)` is highly correlated with `closed_area(teren_zamknięty)` and 8 other fields	High correlation
`district_ Ursus` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Białołęka` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_type_Apartment_high_q(apartamentowiec)` is highly correlated with `closed_area(teren_zamknięty)` and 6 other fields	High correlation
`build_type_Loft/attic(loft)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_mat_Conreate_slab(wielka_płyta)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`terrace(taras)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`closed_area(teren_zamknięty)` is highly correlated with `internet` and 77 other fields	High correlation
`build_mat_Concreate(beton)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`intercom/videophone(domofon/wideofon)` is highly correlated with `internet` and 77 other fields	High correlation
`district_ Wawer` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`heating_Gas(gazowe)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`heating_Boiler(kotłownia)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Praga-Północ` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`status_Renovation(do remontu)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`garden(ogródek)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`anti-burglary blinds(rolety antywłamaniowe)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Śródmieście` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`garage/parking_space(garaż/miejsce_parkingowe)` is highly correlated with `internet` and 77 other fields	High correlation
`district_ Wilanów` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Bemowo` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_mat_Autoclaved_aerated_concrete(beton_komórkowy)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`furniture(meble)` is highly correlated with `washer(pralka)` and 7 other fields	High correlation
`elevator(winda)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`windows_Aluminum(aluminiowe)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_mat_Reinforced_concrete(żelbet)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Ursynów` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`windows_Plastic(plastikowe)` is highly correlated with `closed_area(teren_zamknięty)` and 6 other fields	High correlation
`district_ Wola` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`heating_Central(miejskie)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`heating_Electric(elektryczne)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`balcony(balkon)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`two-level(dwupoziomowe)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Mokotów` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`basement(piwnica)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_mat_Brick(cegła)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Rembertów` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Targówek` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Centrum` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`status_Not_ready_yet(do_wykończenia)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_type_Private_house_1+_fam(szeregowiec)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`monitoring/security(monitoring/ochrona)` is highly correlated with `internet` and 77 other fields	High correlation
`district_ Ochota` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_mat_Wood(drewno)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`available for students(wynajmę również studentom)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_mat_Silicate brick(silikat)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Wesoła` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_mat_Expanded_clay(keramzyt)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`telephone(telefon)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Bielany` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_mat_Concrete_masonry_unit(pustak)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`stove(kuchenka)` is highly correlated with `washer(pralka)` and 7 other fields	High correlation
`poddasze` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`alarm system(system alarmowy)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`cable TV(telewizja kablowa)` is highly correlated with `internet` and 6 other fields	High correlation
`dish_washer(zmywarka)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`status_Ready(do_zamieszkania)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`separate kitchen(oddzielna kuchnia)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`district_ Warszawa` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`windows_Wooden(drewniane)` is highly correlated with `closed_area(teren_zamknięty)` and 6 other fields	High correlation
`secure_doors/windows(drzwi/okna_antywłamaniowe)` is highly correlated with `internet` and 77 other fields	High correlation
`build_type_Apartment_medium_q(blok)` is highly correlated with `build_type_Apartment_high_q(apartamentowiec)` and 6 other fields	High correlation
`tv_set(telewizor)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`build_type_Tenement(kamienica)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`utility room(pom. użytkowe)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`air conditioning(klimatyzacja)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`heating_Other(inne)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`only_for_non-smokers(tylko_dla_niepalących)` is highly correlated with `internet` and 77 other fields	High correlation
`district_ Włochy` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`fridge(lodówka)` is highly correlated with `washer(pralka)` and 8 other fields	High correlation
`oven(piekarnik)` is highly correlated with `closed_area(teren_zamknięty)` and 5 other fields	High correlation
`year_built` is highly skewed (γ1 = 45.58472383)	Skewed

Reproduction

Analysis started	2021-05-25 11:06:42.233093
Analysis finished	2021-05-25 11:07:28.796975
Duration	46.56 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

area
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	117
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	45.45766129

Minimum	3
Maximum	220
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.2 KiB

Quantile statistics

Minimum	3
5-th percentile	25
Q1	35
median	42
Q3	53
95-th percentile	76
Maximum	220
Range	217
Interquartile range (IQR)	18

Descriptive statistics

Standard deviation	17.59378521
Coefficient of variation (CV)	0.3870367439
Kurtosis	10.61048437
Mean	45.45766129
Median Absolute Deviation (MAD)	8
Skewness	2.150144635
Sum	157829
Variance	309.5412781
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50	175	5.0%
40	174	5.0%
38	167	4.8%
42	127	3.7%
30	120	3.5%
45	111	3.2%
35	108	3.1%
37	104	3.0%
48	102	2.9%
36	95	2.7%
Other values (107)	2189	63.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3	1	< 0.1%
10	3	0.1%
12	5	0.1%
13	1	< 0.1%
14	2	0.1%
15	2	0.1%
16	10	0.3%
17	9	0.3%
18	11	0.3%
19	9	0.3%

Value	Count	Frequency (%)
220	1	< 0.1%
200	1	< 0.1%
181	1	< 0.1%
180	1	< 0.1%
166	1	< 0.1%
160	1	< 0.1%
150	1	< 0.1%
147	1	< 0.1%
140	3	0.1%
134	1	< 0.1%

room_num
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.98531106

Minimum	1
Maximum	7
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.2 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	2
95-th percentile	3
Maximum	7
Range	6
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.7464987639
Coefficient of variation (CV)	0.3760109834
Kurtosis	1.734106779
Mean	1.98531106
Median Absolute Deviation (MAD)	0
Skewness	0.8053912206
Sum	6893
Variance	0.5572604045
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
2	1990	57.3%
1	834	24.0%
3	533	15.4%
4	98	2.8%
5	15	0.4%
6	1	< 0.1%
7	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	834	24.0%
2	1990	57.3%
3	533	15.4%
4	98	2.8%
5	15	0.4%
6	1	< 0.1%
7	1	< 0.1%

Value	Count	Frequency (%)
7	1	< 0.1%
6	1	< 0.1%
5	15	0.4%
4	98	2.8%
3	533	15.4%
2	1990	57.3%
1	834	24.0%

floor
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	60
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.525101141

Minimum	0
Maximum	15
Zeros	4
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	27.2 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	3
Q3	5
95-th percentile	9
Maximum	15
Range	15
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.612843215
Coefficient of variation (CV)	0.7412108504
Kurtosis	0.6993925188
Mean	3.525101141
Median Absolute Deviation (MAD)	2
Skewness	1.160178722
Sum	12239.15116
Variance	6.826949665
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	945	27.2%
2	604	17.4%
3	517	14.9%
4	369	10.6%
5	265	7.6%
6	205	5.9%
7	134	3.9%
8	111	3.2%
11	86	2.5%
9	80	2.3%
Other values (50)	156	4.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4	0.1%
1	945	27.2%
2	604	17.4%
2.813953488	1	< 0.1%
3	517	14.9%
3.046511628	1	< 0.1%
3.058139535	1	< 0.1%
3.093023256	2	0.1%
3.104651163	1	< 0.1%
3.151162791	1	< 0.1%

Value	Count	Frequency (%)
15	1	< 0.1%
11	86	2.5%
10	71	2.0%
9	80	2.3%
8	111	3.2%
7	134	3.9%
6	205	5.9%
5	265	7.6%
4.290697674	1	< 0.1%
4.209302326	1	< 0.1%

total_floor
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	171
Distinct (%)	4.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.530389294

Minimum	1
Maximum	30
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.2 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	4
median	6
Q3	8
95-th percentile	13
Maximum	30
Range	29
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	3.336553173
Coefficient of variation (CV)	0.5109271474
Kurtosis	4.146994142
Mean	6.530389294
Median Absolute Deviation (MAD)	2
Skewness	1.496243399
Sum	22673.51163
Variance	11.13258708
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4	617	17.8%
6	387	11.1%
3	343	9.9%
5	314	9.0%
10	301	8.7%
7	265	7.6%
8	234	6.7%
2	130	3.7%
15	86	2.5%
11	85	2.4%
Other values (161)	710	20.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	28	0.8%
2	130	3.7%
3	343	9.9%
4	617	17.8%
5	314	9.0%
5.151162791	1	< 0.1%
5.162790698	1	< 0.1%
5.174418605	1	< 0.1%
5.197674419	1	< 0.1%
5.220930233	1	< 0.1%

Value	Count	Frequency (%)
30	3	0.1%
25	2	0.1%
24	1	< 0.1%
23	1	< 0.1%
22	6	0.2%
21	1	< 0.1%
20	2	0.1%
19	3	0.1%
18	1	< 0.1%
17	19	0.5%

year_built
Real number (ℝ_≥0)

SKEWED

Distinct	796
Distinct (%)	22.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2010.896005

Minimum	1890
Maximum	20202
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.2 KiB

Quantile statistics

Minimum	1890
5-th percentile	1950
Q1	1992
median	2004.319767
Q3	2017
95-th percentile	2020
Maximum	20202
Range	18312
Interquartile range (IQR)	25

Descriptive statistics

Standard deviation	353.9073609
Coefficient of variation (CV)	0.17599486
Kurtosis	2192.941651
Mean	2010.896005
Median Absolute Deviation (MAD)	12.43604651
Skewness	45.58472383
Sum	6981830.93
Variance	125250.4201
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2020	334	9.6%
2019	164	4.7%
2018	129	3.7%
2017	116	3.3%
2008	93	2.7%
2010	91	2.6%
2016	89	2.6%
1970	77	2.2%
2015	75	2.2%
2000	68	2.0%
Other values (786)	2236	64.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1890	2	0.1%
1900	2	0.1%
1901	2	0.1%
1903	1	< 0.1%
1904	2	0.1%
1905	1	< 0.1%
1906	1	< 0.1%
1910	2	0.1%
1912	4	0.1%
1913	2	0.1%

Value	Count	Frequency (%)
20202	1	< 0.1%
11976	1	< 0.1%
2219.244186	1	< 0.1%
2217.418605	1	< 0.1%
2217.372093	3	0.1%
2217.069767	1	< 0.1%
2216.906977	1	< 0.1%
2216.569767	1	< 0.1%
2216.476744	1	< 0.1%
2215.988372	1	< 0.1%

poddasze
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3465
1.0	7

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3465	99.8%
1.0	7	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3465	99.8%
1.0	7	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	6937	66.6%
.	3472	33.3%
1	7	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6937	99.9%
1	7	0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6937	66.6%
.	3472	33.3%
1	7	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6937	66.6%
.	3472	33.3%
1	7	0.1%

dish_washer(zmywarka)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	2160
0.0	1312

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2160	62.2%
0.0	1312	37.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2160	62.2%
0.0	1312	37.8%

Most occurring characters

Value	Count	Frequency (%)
0	4784	45.9%
.	3472	33.3%
1	2160	20.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4784	68.9%
1	2160	31.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4784	45.9%
.	3472	33.3%
1	2160	20.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4784	45.9%
.	3472	33.3%
1	2160	20.7%

fridge(lodówka)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	3374
0.0	98

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	3374	97.2%
0.0	98	2.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	3374	97.2%
0.0	98	2.8%

Most occurring characters

Value	Count	Frequency (%)
0	3570	34.3%
.	3472	33.3%
1	3374	32.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3570	51.4%
1	3374	48.6%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3570	34.3%
.	3472	33.3%
1	3374	32.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3570	34.3%
.	3472	33.3%
1	3374	32.4%

furniture(meble)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	3259
0.0	213

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	3259	93.9%
0.0	213	6.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	3259	93.9%
0.0	213	6.1%

Most occurring characters

Value	Count	Frequency (%)
0	3685	35.4%
.	3472	33.3%
1	3259	31.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3685	53.1%
1	3259	46.9%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3685	35.4%
.	3472	33.3%
1	3259	31.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3685	35.4%
.	3472	33.3%
1	3259	31.3%

oven(piekarnik)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	2898
0.0	574

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2898	83.5%
0.0	574	16.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2898	83.5%
0.0	574	16.5%

Most occurring characters

Value	Count	Frequency (%)
0	4046	38.8%
.	3472	33.3%
1	2898	27.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4046	58.3%
1	2898	41.7%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4046	38.8%
.	3472	33.3%
1	2898	27.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4046	38.8%
.	3472	33.3%
1	2898	27.8%

stove(kuchenka)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	3272
0.0	200

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	3272	94.2%
0.0	200	5.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	3272	94.2%
0.0	200	5.8%

Most occurring characters

Value	Count	Frequency (%)
0	3672	35.3%
.	3472	33.3%
1	3272	31.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3672	52.9%
1	3272	47.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3672	35.3%
.	3472	33.3%
1	3272	31.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3672	35.3%
.	3472	33.3%
1	3272	31.4%

tv_set(telewizor)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	1817
1.0	1655

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	1.0
4th row	1.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	1817	52.3%
1.0	1655	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	1817	52.3%
1.0	1655	47.7%

Most occurring characters

Value	Count	Frequency (%)
0	5289	50.8%
.	3472	33.3%
1	1655	15.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5289	76.2%
1	1655	23.8%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5289	50.8%
.	3472	33.3%
1	1655	15.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5289	50.8%
.	3472	33.3%
1	1655	15.9%

washer(pralka)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	3319
0.0	153

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	3319	95.6%
0.0	153	4.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	3319	95.6%
0.0	153	4.4%

Most occurring characters

Value	Count	Frequency (%)
0	3625	34.8%
.	3472	33.3%
1	3319	31.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3625	52.2%
1	3319	47.8%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3625	34.8%
.	3472	33.3%
1	3319	31.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3625	34.8%
.	3472	33.3%
1	3319	31.9%

secure_doors/windows(drzwi/okna_antywłamaniowe)
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3472

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3472	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3472	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6944	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

intercom/videophone(domofon/wideofon)
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3472

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3472	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3472	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6944	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

monitoring/security(monitoring/ochrona)
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3472

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3472	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3472	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6944	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

closed_area(teren_zamknięty)
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3472

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3472	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3472	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6944	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

balcony(balkon)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	2358
0.0	1114

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	1.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	2358	67.9%
0.0	1114	32.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2358	67.9%
0.0	1114	32.1%

Most occurring characters

Value	Count	Frequency (%)
0	4586	44.0%
.	3472	33.3%
1	2358	22.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4586	66.0%
1	2358	34.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4586	44.0%
.	3472	33.3%
1	2358	22.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4586	44.0%
.	3472	33.3%
1	2358	22.6%

basement(piwnica)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2683
1.0	789

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	2683	77.3%
1.0	789	22.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2683	77.3%
1.0	789	22.7%

Most occurring characters

Value	Count	Frequency (%)
0	6155	59.1%
.	3472	33.3%
1	789	7.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6155	88.6%
1	789	11.4%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6155	59.1%
.	3472	33.3%
1	789	7.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6155	59.1%
.	3472	33.3%
1	789	7.6%

garage/parking_space(garaż/miejsce_parkingowe)
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3472

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3472	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3472	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6944	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

alarm system(system alarmowy)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3319
1.0	153

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3319	95.6%
1.0	153	4.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3319	95.6%
1.0	153	4.4%

Most occurring characters

Value	Count	Frequency (%)
0	6791	65.2%
.	3472	33.3%
1	153	1.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6791	97.8%
1	153	2.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6791	65.2%
.	3472	33.3%
1	153	1.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6791	65.2%
.	3472	33.3%
1	153	1.5%

only_for_non-smokers(tylko_dla_niepalących)
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3472

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3472	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3472	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6944	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6944	66.7%
.	3472	33.3%

anti-burglary blinds(rolety antywłamaniowe)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3387
1.0	85

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3387	97.6%
1.0	85	2.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3387	97.6%
1.0	85	2.4%

Most occurring characters

Value	Count	Frequency (%)
0	6859	65.9%
.	3472	33.3%
1	85	0.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6859	98.8%
1	85	1.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6859	65.9%
.	3472	33.3%
1	85	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6859	65.9%
.	3472	33.3%
1	85	0.8%

elevator(winda)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	2304
0.0	1168

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2304	66.4%
0.0	1168	33.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2304	66.4%
0.0	1168	33.6%

Most occurring characters

Value	Count	Frequency (%)
0	4640	44.5%
.	3472	33.3%
1	2304	22.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4640	66.8%
1	2304	33.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4640	44.5%
.	3472	33.3%
1	2304	22.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4640	44.5%
.	3472	33.3%
1	2304	22.1%

separate kitchen(oddzielna kuchnia)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2418
1.0	1054

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	2418	69.6%
1.0	1054	30.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2418	69.6%
1.0	1054	30.4%

Most occurring characters

Value	Count	Frequency (%)
0	5890	56.5%
.	3472	33.3%
1	1054	10.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5890	84.8%
1	1054	15.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5890	56.5%
.	3472	33.3%
1	1054	10.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5890	56.5%
.	3472	33.3%
1	1054	10.1%

internet
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	1902
1.0	1570

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	1902	54.8%
1.0	1570	45.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	1902	54.8%
1.0	1570	45.2%

Most occurring characters

Value	Count	Frequency (%)
0	5374	51.6%
.	3472	33.3%
1	1570	15.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5374	77.4%
1	1570	22.6%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5374	51.6%
.	3472	33.3%
1	1570	15.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5374	51.6%
.	3472	33.3%
1	1570	15.1%

cable TV(telewizja kablowa)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2118
1.0	1354

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	2118	61.0%
1.0	1354	39.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2118	61.0%
1.0	1354	39.0%

Most occurring characters

Value	Count	Frequency (%)
0	5590	53.7%
.	3472	33.3%
1	1354	13.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5590	80.5%
1	1354	19.5%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5590	53.7%
.	3472	33.3%
1	1354	13.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5590	53.7%
.	3472	33.3%
1	1354	13.0%

telephone(telefon)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3080
1.0	392

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3080	88.7%
1.0	392	11.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3080	88.7%
1.0	392	11.3%

Most occurring characters

Value	Count	Frequency (%)
0	6552	62.9%
.	3472	33.3%
1	392	3.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6552	94.4%
1	392	5.6%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6552	62.9%
.	3472	33.3%
1	392	3.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6552	62.9%
.	3472	33.3%
1	392	3.8%

air conditioning(klimatyzacja)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3117
1.0	355

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3117	89.8%
1.0	355	10.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3117	89.8%
1.0	355	10.2%

Most occurring characters

Value	Count	Frequency (%)
0	6589	63.3%
.	3472	33.3%
1	355	3.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6589	94.9%
1	355	5.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6589	63.3%
.	3472	33.3%
1	355	3.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6589	63.3%
.	3472	33.3%
1	355	3.4%

available for students(wynajmę również studentom)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2939
1.0	533

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	2939	84.6%
1.0	533	15.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2939	84.6%
1.0	533	15.4%

Most occurring characters

Value	Count	Frequency (%)
0	6411	61.5%
.	3472	33.3%
1	533	5.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6411	92.3%
1	533	7.7%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6411	61.5%
.	3472	33.3%
1	533	5.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6411	61.5%
.	3472	33.3%
1	533	5.1%

utility room(pom. użytkowe)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3097
1.0	375

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3097	89.2%
1.0	375	10.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3097	89.2%
1.0	375	10.8%

Most occurring characters

Value	Count	Frequency (%)
0	6569	63.1%
.	3472	33.3%
1	375	3.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6569	94.6%
1	375	5.4%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6569	63.1%
.	3472	33.3%
1	375	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6569	63.1%
.	3472	33.3%
1	375	3.6%

terrace(taras)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3105
1.0	367

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3105	89.4%
1.0	367	10.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3105	89.4%
1.0	367	10.6%

Most occurring characters

Value	Count	Frequency (%)
0	6577	63.1%
.	3472	33.3%
1	367	3.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6577	94.7%
1	367	5.3%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6577	63.1%
.	3472	33.3%
1	367	3.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6577	63.1%
.	3472	33.3%
1	367	3.5%

two-level(dwupoziomowe)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3438
1.0	34

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3438	99.0%
1.0	34	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3438	99.0%
1.0	34	1.0%

Most occurring characters

Value	Count	Frequency (%)
0	6910	66.3%
.	3472	33.3%
1	34	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6910	99.5%
1	34	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6910	66.3%
.	3472	33.3%
1	34	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6910	66.3%
.	3472	33.3%
1	34	0.3%

garden(ogródek)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3278
1.0	194

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3278	94.4%
1.0	194	5.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3278	94.4%
1.0	194	5.6%

Most occurring characters

Value	Count	Frequency (%)
0	6750	64.8%
.	3472	33.3%
1	194	1.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6750	97.2%
1	194	2.8%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6750	64.8%
.	3472	33.3%
1	194	1.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6750	64.8%
.	3472	33.3%
1	194	1.9%

build_type_Apartment_high_q(apartamentowiec)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2436
1.0	1036

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	2436	70.2%
1.0	1036	29.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2436	70.2%
1.0	1036	29.8%

Most occurring characters

Value	Count	Frequency (%)
0	5908	56.7%
.	3472	33.3%
1	1036	9.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5908	85.1%
1	1036	14.9%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5908	56.7%
.	3472	33.3%
1	1036	9.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5908	56.7%
.	3472	33.3%
1	1036	9.9%

build_type_Apartment_medium_q(blok)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	1837
0.0	1635

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	1837	52.9%
0.0	1635	47.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	1837	52.9%
0.0	1635	47.1%

Most occurring characters

Value	Count	Frequency (%)
0	5107	49.0%
.	3472	33.3%
1	1837	17.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5107	73.5%
1	1837	26.5%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5107	49.0%
.	3472	33.3%
1	1837	17.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5107	49.0%
.	3472	33.3%
1	1837	17.6%

build_type_Infill(plomba)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3469
1.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3469	99.9%
1.0	3	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3469	99.9%
1.0	3	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	6941	66.6%
.	3472	33.3%
1	3	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6941	> 99.9%
1	3	< 0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6941	66.6%
.	3472	33.3%
1	3	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6941	66.6%
.	3472	33.3%
1	3	< 0.1%

build_type_Loft/attic(loft)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3468
1.0	4

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3468	99.9%
1.0	4	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3468	99.9%
1.0	4	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	6940	66.6%
.	3472	33.3%
1	4	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6940	99.9%
1	4	0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6940	66.6%
.	3472	33.3%
1	4	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6940	66.6%
.	3472	33.3%
1	4	< 0.1%

build_type_Private_house_1+_fam(szeregowiec)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3462
1.0	10

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3462	99.7%
1.0	10	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3462	99.7%
1.0	10	0.3%

Most occurring characters

Value	Count	Frequency (%)
0	6934	66.6%
.	3472	33.3%
1	10	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6934	99.9%
1	10	0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6934	66.6%
.	3472	33.3%
1	10	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6934	66.6%
.	3472	33.3%
1	10	0.1%

build_type_Private_house_1_fam(dom wolnostojący)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3450
1.0	22

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3450	99.4%
1.0	22	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3450	99.4%
1.0	22	0.6%

Most occurring characters

Value	Count	Frequency (%)
0	6922	66.5%
.	3472	33.3%
1	22	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6922	99.7%
1	22	0.3%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6922	66.5%
.	3472	33.3%
1	22	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6922	66.5%
.	3472	33.3%
1	22	0.2%

build_type_Tenement(kamienica)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3054
1.0	418

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	3054	88.0%
1.0	418	12.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3054	88.0%
1.0	418	12.0%

Most occurring characters

Value	Count	Frequency (%)
0	6526	62.7%
.	3472	33.3%
1	418	4.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6526	94.0%
1	418	6.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6526	62.7%
.	3472	33.3%
1	418	4.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6526	62.7%
.	3472	33.3%
1	418	4.0%

build_mat_Autoclaved_aerated_concrete(beton_komórkowy)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3416
1.0	56

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3416	98.4%
1.0	56	1.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3416	98.4%
1.0	56	1.6%

Most occurring characters

Value	Count	Frequency (%)
0	6888	66.1%
.	3472	33.3%
1	56	0.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6888	99.2%
1	56	0.8%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6888	66.1%
.	3472	33.3%
1	56	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6888	66.1%
.	3472	33.3%
1	56	0.5%

build_mat_Brick(cegła)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2022
1.0	1450

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	2022	58.2%
1.0	1450	41.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2022	58.2%
1.0	1450	41.8%

Most occurring characters

Value	Count	Frequency (%)
0	5494	52.7%
.	3472	33.3%
1	1450	13.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5494	79.1%
1	1450	20.9%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5494	52.7%
.	3472	33.3%
1	1450	13.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5494	52.7%
.	3472	33.3%
1	1450	13.9%

build_mat_Concreate(beton)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3378
1.0	94

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3378	97.3%
1.0	94	2.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3378	97.3%
1.0	94	2.7%

Most occurring characters

Value	Count	Frequency (%)
0	6850	65.8%
.	3472	33.3%
1	94	0.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6850	98.6%
1	94	1.4%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6850	65.8%
.	3472	33.3%
1	94	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6850	65.8%
.	3472	33.3%
1	94	0.9%

build_mat_Concrete_masonry_unit(pustak)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3373
1.0	99

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3373	97.1%
1.0	99	2.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3373	97.1%
1.0	99	2.9%

Most occurring characters

Value	Count	Frequency (%)
0	6845	65.7%
.	3472	33.3%
1	99	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6845	98.6%
1	99	1.4%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6845	65.7%
.	3472	33.3%
1	99	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6845	65.7%
.	3472	33.3%
1	99	1.0%

build_mat_Conreate_slab(wielka_płyta)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3231
1.0	241

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3231	93.1%
1.0	241	6.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3231	93.1%
1.0	241	6.9%

Most occurring characters

Value	Count	Frequency (%)
0	6703	64.4%
.	3472	33.3%
1	241	2.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6703	96.5%
1	241	3.5%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6703	64.4%
.	3472	33.3%
1	241	2.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6703	64.4%
.	3472	33.3%
1	241	2.3%

build_mat_Expanded_clay(keramzyt)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3470
1.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3470	99.9%
1.0	2	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3470	99.9%
1.0	2	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6942	> 99.9%
1	2	< 0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

build_mat_Other(inne)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3345
1.0	127

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3345	96.3%
1.0	127	3.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3345	96.3%
1.0	127	3.7%

Most occurring characters

Value	Count	Frequency (%)
0	6817	65.4%
.	3472	33.3%
1	127	1.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6817	98.2%
1	127	1.8%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6817	65.4%
.	3472	33.3%
1	127	1.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6817	65.4%
.	3472	33.3%
1	127	1.2%

build_mat_Reinforced_concrete(żelbet)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3349
1.0	123

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3349	96.5%
1.0	123	3.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3349	96.5%
1.0	123	3.5%

Most occurring characters

Value	Count	Frequency (%)
0	6821	65.5%
.	3472	33.3%
1	123	1.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6821	98.2%
1	123	1.8%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6821	65.5%
.	3472	33.3%
1	123	1.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6821	65.5%
.	3472	33.3%
1	123	1.2%

build_mat_Silicate brick(silikat)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3433
1.0	39

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3433	98.9%
1.0	39	1.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3433	98.9%
1.0	39	1.1%

Most occurring characters

Value	Count	Frequency (%)
0	6905	66.3%
.	3472	33.3%
1	39	0.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6905	99.4%
1	39	0.6%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6905	66.3%
.	3472	33.3%
1	39	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6905	66.3%
.	3472	33.3%
1	39	0.4%

build_mat_Wood(drewno)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3470
1.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3470	99.9%
1.0	2	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3470	99.9%
1.0	2	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6942	> 99.9%
1	2	< 0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

windows_Aluminum(aluminiowe)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3436
1.0	36

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3436	99.0%
1.0	36	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3436	99.0%
1.0	36	1.0%

Most occurring characters

Value	Count	Frequency (%)
0	6908	66.3%
.	3472	33.3%
1	36	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6908	99.5%
1	36	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6908	66.3%
.	3472	33.3%
1	36	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6908	66.3%
.	3472	33.3%
1	36	0.3%

windows_Plastic(plastikowe)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	2148
0.0	1324

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2148	61.9%
0.0	1324	38.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2148	61.9%
0.0	1324	38.1%

Most occurring characters

Value	Count	Frequency (%)
0	4796	46.0%
.	3472	33.3%
1	2148	20.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4796	69.1%
1	2148	30.9%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4796	46.0%
.	3472	33.3%
1	2148	20.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4796	46.0%
.	3472	33.3%
1	2148	20.6%

windows_Wooden(drewniane)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2764
1.0	708

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	1.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	2764	79.6%
1.0	708	20.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2764	79.6%
1.0	708	20.4%

Most occurring characters

Value	Count	Frequency (%)
0	6236	59.9%
.	3472	33.3%
1	708	6.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6236	89.8%
1	708	10.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6236	59.9%
.	3472	33.3%
1	708	6.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6236	59.9%
.	3472	33.3%
1	708	6.8%

heating_Boiler(kotłownia)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3404
1.0	68

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3404	98.0%
1.0	68	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3404	98.0%
1.0	68	2.0%

Most occurring characters

Value	Count	Frequency (%)
0	6876	66.0%
.	3472	33.3%
1	68	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6876	99.0%
1	68	1.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6876	66.0%
.	3472	33.3%
1	68	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6876	66.0%
.	3472	33.3%
1	68	0.7%

heating_Central(miejskie)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	2775
0.0	697

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2775	79.9%
0.0	697	20.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2775	79.9%
0.0	697	20.1%

Most occurring characters

Value	Count	Frequency (%)
0	4169	40.0%
.	3472	33.3%
1	2775	26.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4169	60.0%
1	2775	40.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4169	40.0%
.	3472	33.3%
1	2775	26.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4169	40.0%
.	3472	33.3%
1	2775	26.6%

heating_Electric(elektryczne)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3450
1.0	22

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3450	99.4%
1.0	22	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3450	99.4%
1.0	22	0.6%

Most occurring characters

Value	Count	Frequency (%)
0	6922	66.5%
.	3472	33.3%
1	22	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6922	99.7%
1	22	0.3%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6922	66.5%
.	3472	33.3%
1	22	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6922	66.5%
.	3472	33.3%
1	22	0.2%

heating_Gas(gazowe)
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3363
1.0	109

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3363	96.9%
1.0	109	3.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3363	96.9%
1.0	109	3.1%

Most occurring characters

Value	Count	Frequency (%)
0	6835	65.6%
.	3472	33.3%
1	109	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6835	98.4%
1	109	1.6%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6835	65.6%
.	3472	33.3%
1	109	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6835	65.6%
.	3472	33.3%
1	109	1.0%

heating_Other(inne)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3456
1.0	16

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3456	99.5%
1.0	16	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3456	99.5%
1.0	16	0.5%

Most occurring characters

Value	Count	Frequency (%)
0	6928	66.5%
.	3472	33.3%
1	16	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6928	99.8%
1	16	0.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6928	66.5%
.	3472	33.3%
1	16	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6928	66.5%
.	3472	33.3%
1	16	0.2%

status_Not_ready_yet(do_wykończenia)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3466
1.0	6

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3466	99.8%
1.0	6	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3466	99.8%
1.0	6	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	6938	66.6%
.	3472	33.3%
1	6	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6938	99.9%
1	6	0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6938	66.6%
.	3472	33.3%
1	6	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6938	66.6%
.	3472	33.3%
1	6	0.1%

status_Ready(do_zamieszkania)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

1.0	3175
0.0	297

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	3175	91.4%
0.0	297	8.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	3175	91.4%
0.0	297	8.6%

Most occurring characters

Value	Count	Frequency (%)
0	3769	36.2%
.	3472	33.3%
1	3175	30.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3769	54.3%
1	3175	45.7%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3769	36.2%
.	3472	33.3%
1	3175	30.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3769	36.2%
.	3472	33.3%
1	3175	30.5%

status_Renovation(do remontu)
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3470
1.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3470	99.9%
1.0	2	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3470	99.9%
1.0	2	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6942	> 99.9%
1	2	< 0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

district_ Bemowo
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3317
1.0	155

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3317	95.5%
1.0	155	4.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3317	95.5%
1.0	155	4.5%

Most occurring characters

Value	Count	Frequency (%)
0	6789	65.2%
.	3472	33.3%
1	155	1.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6789	97.8%
1	155	2.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6789	65.2%
.	3472	33.3%
1	155	1.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6789	65.2%
.	3472	33.3%
1	155	1.5%

district_ Białołęka
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3317
1.0	155

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3317	95.5%
1.0	155	4.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3317	95.5%
1.0	155	4.5%

Most occurring characters

Value	Count	Frequency (%)
0	6789	65.2%
.	3472	33.3%
1	155	1.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6789	97.8%
1	155	2.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6789	65.2%
.	3472	33.3%
1	155	1.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6789	65.2%
.	3472	33.3%
1	155	1.5%

district_ Bielany
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3306
1.0	166

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3306	95.2%
1.0	166	4.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3306	95.2%
1.0	166	4.8%

Most occurring characters

Value	Count	Frequency (%)
0	6778	65.1%
.	3472	33.3%
1	166	1.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6778	97.6%
1	166	2.4%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6778	65.1%
.	3472	33.3%
1	166	1.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6778	65.1%
.	3472	33.3%
1	166	1.6%

district_ Centrum
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3412
1.0	60

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3412	98.3%
1.0	60	1.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3412	98.3%
1.0	60	1.7%

Most occurring characters

Value	Count	Frequency (%)
0	6884	66.1%
.	3472	33.3%
1	60	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6884	99.1%
1	60	0.9%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6884	66.1%
.	3472	33.3%
1	60	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6884	66.1%
.	3472	33.3%
1	60	0.6%

district_ Metro Wilanowska
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3470
1.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3470	99.9%
1.0	2	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3470	99.9%
1.0	2	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6942	> 99.9%
1	2	< 0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6942	66.6%
.	3472	33.3%
1	2	< 0.1%

district_ Mokotów
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2825
1.0	647

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	2825	81.4%
1.0	647	18.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2825	81.4%
1.0	647	18.6%

Most occurring characters

Value	Count	Frequency (%)
0	6297	60.5%
.	3472	33.3%
1	647	6.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6297	90.7%
1	647	9.3%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6297	60.5%
.	3472	33.3%
1	647	6.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6297	60.5%
.	3472	33.3%
1	647	6.2%

district_ Ochota
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3271
1.0	201

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	3271	94.2%
1.0	201	5.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3271	94.2%
1.0	201	5.8%

Most occurring characters

Value	Count	Frequency (%)
0	6743	64.7%
.	3472	33.3%
1	201	1.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6743	97.1%
1	201	2.9%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6743	64.7%
.	3472	33.3%
1	201	1.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6743	64.7%
.	3472	33.3%
1	201	1.9%

district_ Praga-Południe
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3233
1.0	239

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3233	93.1%
1.0	239	6.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3233	93.1%
1.0	239	6.9%

Most occurring characters

Value	Count	Frequency (%)
0	6705	64.4%
.	3472	33.3%
1	239	2.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6705	96.6%
1	239	3.4%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6705	64.4%
.	3472	33.3%
1	239	2.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6705	64.4%
.	3472	33.3%
1	239	2.3%

district_ Praga-Północ
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3337
1.0	135

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3337	96.1%
1.0	135	3.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3337	96.1%
1.0	135	3.9%

Most occurring characters

Value	Count	Frequency (%)
0	6809	65.4%
.	3472	33.3%
1	135	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6809	98.1%
1	135	1.9%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6809	65.4%
.	3472	33.3%
1	135	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6809	65.4%
.	3472	33.3%
1	135	1.3%

district_ Rembertów
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3458
1.0	14

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3458	99.6%
1.0	14	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3458	99.6%
1.0	14	0.4%

Most occurring characters

Value	Count	Frequency (%)
0	6930	66.5%
.	3472	33.3%
1	14	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6930	99.8%
1	14	0.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6930	66.5%
.	3472	33.3%
1	14	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6930	66.5%
.	3472	33.3%
1	14	0.1%

district_ Targówek
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3356
1.0	116

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	1.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3356	96.7%
1.0	116	3.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3356	96.7%
1.0	116	3.3%

Most occurring characters

Value	Count	Frequency (%)
0	6828	65.6%
.	3472	33.3%
1	116	1.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6828	98.3%
1	116	1.7%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6828	65.6%
.	3472	33.3%
1	116	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6828	65.6%
.	3472	33.3%
1	116	1.1%

district_ Ursus
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3375
1.0	97

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3375	97.2%
1.0	97	2.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3375	97.2%
1.0	97	2.8%

Most occurring characters

Value	Count	Frequency (%)
0	6847	65.7%
.	3472	33.3%
1	97	0.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6847	98.6%
1	97	1.4%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6847	65.7%
.	3472	33.3%
1	97	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6847	65.7%
.	3472	33.3%
1	97	0.9%

district_ Ursynów
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3267
1.0	205

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3267	94.1%
1.0	205	5.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3267	94.1%
1.0	205	5.9%

Most occurring characters

Value	Count	Frequency (%)
0	6739	64.7%
.	3472	33.3%
1	205	2.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6739	97.0%
1	205	3.0%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6739	64.7%
.	3472	33.3%
1	205	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6739	64.7%
.	3472	33.3%
1	205	2.0%

district_ Warszawa
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3453
1.0	19

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3453	99.5%
1.0	19	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3453	99.5%
1.0	19	0.5%

Most occurring characters

Value	Count	Frequency (%)
0	6925	66.5%
.	3472	33.3%
1	19	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6925	99.7%
1	19	0.3%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6925	66.5%
.	3472	33.3%
1	19	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6925	66.5%
.	3472	33.3%
1	19	0.2%

district_ Wawer
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3430
1.0	42

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3430	98.8%
1.0	42	1.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3430	98.8%
1.0	42	1.2%

Most occurring characters

Value	Count	Frequency (%)
0	6902	66.3%
.	3472	33.3%
1	42	0.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6902	99.4%
1	42	0.6%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6902	66.3%
.	3472	33.3%
1	42	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6902	66.3%
.	3472	33.3%
1	42	0.4%

district_ Wesoła
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3458
1.0	14

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3458	99.6%
1.0	14	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3458	99.6%
1.0	14	0.4%

Most occurring characters

Value	Count	Frequency (%)
0	6930	66.5%
.	3472	33.3%
1	14	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6930	99.8%
1	14	0.2%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6930	66.5%
.	3472	33.3%
1	14	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6930	66.5%
.	3472	33.3%
1	14	0.1%

district_ Wilanów
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3347
1.0	125

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3347	96.4%
1.0	125	3.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3347	96.4%
1.0	125	3.6%

Most occurring characters

Value	Count	Frequency (%)
0	6819	65.5%
.	3472	33.3%
1	125	1.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6819	98.2%
1	125	1.8%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6819	65.5%
.	3472	33.3%
1	125	1.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6819	65.5%
.	3472	33.3%
1	125	1.2%

district_ Wola
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	2960
1.0	512

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	2960	85.3%
1.0	512	14.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2960	85.3%
1.0	512	14.7%

Most occurring characters

Value	Count	Frequency (%)
0	6432	61.8%
.	3472	33.3%
1	512	4.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6432	92.6%
1	512	7.4%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6432	61.8%
.	3472	33.3%
1	512	4.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6432	61.8%
.	3472	33.3%
1	512	4.9%

district_ Włochy
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3395
1.0	77

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3395	97.8%
1.0	77	2.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3395	97.8%
1.0	77	2.2%

Most occurring characters

Value	Count	Frequency (%)
0	6867	65.9%
.	3472	33.3%
1	77	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6867	98.9%
1	77	1.1%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6867	65.9%
.	3472	33.3%
1	77	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6867	65.9%
.	3472	33.3%
1	77	0.7%

district_ mazowieckie
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3428
1.0	44

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3428	98.7%
1.0	44	1.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3428	98.7%
1.0	44	1.3%

Most occurring characters

Value	Count	Frequency (%)
0	6900	66.2%
.	3472	33.3%
1	44	0.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6900	99.4%
1	44	0.6%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6900	66.2%
.	3472	33.3%
1	44	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6900	66.2%
.	3472	33.3%
1	44	0.4%

district_ Śródmieście
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3130
1.0	342

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3130	90.1%
1.0	342	9.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3130	90.1%
1.0	342	9.9%

Most occurring characters

Value	Count	Frequency (%)
0	6602	63.4%
.	3472	33.3%
1	342	3.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6602	95.1%
1	342	4.9%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6602	63.4%
.	3472	33.3%
1	342	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6602	63.4%
.	3472	33.3%
1	342	3.3%

district_ Żoliborz
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.2 KiB

0.0	3367
1.0	105

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10416
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	3367	97.0%
1.0	105	3.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	3367	97.0%
1.0	105	3.0%

Most occurring characters

Value	Count	Frequency (%)
0	6839	65.7%
.	3472	33.3%
1	105	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6944	66.7%
Other Punctuation	3472	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6839	98.5%
1	105	1.5%

Other Punctuation

Value	Count	Frequency (%)
.	3472	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10416	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6839	65.7%
.	3472	33.3%
1	105	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10416	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6839	65.7%
.	3472	33.3%
1	105	1.0%

gross_price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1256
Distinct (%)	36.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2743.665343

Minimum	581.4186047
Maximum	11500
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.2 KiB

Quantile statistics

Minimum	581.4186047
5-th percentile	1738.40407
Q1	2200
median	2587.476744
Q3	3000
95-th percentile	4391.627326
Maximum	11500
Range	10918.5814
Interquartile range (IQR)	800

Descriptive statistics

Standard deviation	938.3324972
Coefficient of variation (CV)	0.3419996173
Kurtosis	13.4003479
Mean	2743.665343
Median Absolute Deviation (MAD)	412.5232558
Skewness	2.709006919
Sum	9526006.07
Variance	880467.8754
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2500	95	2.7%
2200	80	2.3%
2600	63	1.8%
2300	63	1.8%
2000	62	1.8%
2400	59	1.7%
2100	56	1.6%
3000	49	1.4%
2900	44	1.3%
2700	43	1.2%
Other values (1246)	2858	82.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
581.4186047	1	< 0.1%
588.0465116	1	< 0.1%
773.627907	1	< 0.1%
941.0697674	1	< 0.1%
1032	1	< 0.1%
1120	1	< 0.1%
1140.72093	1	< 0.1%
1150	1	< 0.1%
1198	1	< 0.1%
1199	1	< 0.1%

Value	Count	Frequency (%)
11500	1	< 0.1%
10598.26744	1	< 0.1%
10500	1	< 0.1%
10000	1	< 0.1%
9800	1	< 0.1%
9613.5	1	< 0.1%
9215.418605	1	< 0.1%
9207.674419	1	< 0.1%
8657.674419	1	< 0.1%
8201.569767	2	0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	area	room_num	floor	total_floor	year_built	dish_washer(zmywarka)	fridge(lodówka)	furniture(meble)	oven(piekarnik)	stove(kuchenka)	tv_set(telewizor)	washer(pralka)	balcony(balkon)	basement(piwnica)	elevator(winda)	separate kitchen(oddzielna kuchnia)	internet	cable TV(telewizja kablowa)	air conditioning(klimatyzacja)	utility room(pom. użytkowe)	build_type_Apartment_medium_q(blok)	build_type_Tenement(kamienica)	build_mat_Brick(cegła)	build_mat_Concrete_masonry_unit(pustak)	build_mat_Conreate_slab(wielka_płyta)	windows_Plastic(plastikowe)	windows_Wooden(drewniane)	heating_Central(miejskie)	status_Ready(do_zamieszkania)	district_ Bielany	district_ Mokotów	district_ Ochota	district_ Targówek	district_ Ursynów	district_ Wola	district_ Włochy	district_ Żoliborz	gross_price
0	37.0	2.0	1.0	4.000000	2001.453488	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	2435.244186
1	38.0	2.0	1.0	5.802326	2020.000000	1.0	1.0	1.0	1.0	1.0	0.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	2175.000000
2	57.0	3.0	1.0	15.000000	1984.000000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	3300.000000
3	63.0	2.0	4.0	5.000000	2005.000000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	2585.046512
4	65.0	3.0	3.0	4.000000	1938.000000	1.0	1.0	1.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	3424.918605
5	50.0	2.0	1.0	3.000000	1957.000000	1.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	2918.383721
6	31.0	1.0	5.0	7.000000	1984.476744	0.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	1955.604651
7	20.0	1.0	2.0	4.000000	2000.000000	1.0	1.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1900.000000
8	90.0	3.0	8.0	8.000000	2020.000000	1.0	1.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	4700.000000
9	79.0	3.0	1.0	3.000000	2004.000000	1.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	3000.000000

Last rows

	area	room_num	floor	total_floor	year_built	dish_washer(zmywarka)	fridge(lodówka)	furniture(meble)	oven(piekarnik)	stove(kuchenka)	tv_set(telewizor)	washer(pralka)	balcony(balkon)	basement(piwnica)	elevator(winda)	separate kitchen(oddzielna kuchnia)	internet	cable TV(telewizja kablowa)	telephone(telefon)	available for students(wynajmę również studentom)	utility room(pom. użytkowe)	garden(ogródek)	build_type_Apartment_high_q(apartamentowiec)	build_type_Apartment_medium_q(blok)	build_type_Tenement(kamienica)	build_mat_Brick(cegła)	build_mat_Concreate(beton)	build_mat_Conreate_slab(wielka_płyta)	windows_Plastic(plastikowe)	windows_Wooden(drewniane)	heating_Boiler(kotłownia)	heating_Central(miejskie)	status_Ready(do_zamieszkania)	district_ Białołęka	district_ Mokotów	district_ Praga-Południe	district_ Praga-Północ	district_ Ursynów	district_ Wilanów	district_ Śródmieście	gross_price
3462	58.0	2.0	4.0	6.0	1962.000000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	2950.000000
3463	28.0	2.0	1.0	15.0	1972.000000	0.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	2200.000000
3464	44.0	2.0	1.0	3.0	2020.000000	1.0	1.0	1.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	2150.000000
3465	40.0	1.0	1.0	4.0	2000.000000	0.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1860.000000
3466	39.0	2.0	11.0	15.0	1995.848837	0.0	1.0	1.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	2357.837209
3467	45.0	1.0	3.0	7.0	2002.965116	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	2350.000000
3468	50.0	2.0	1.0	2.0	2006.000000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	3737.302326
3469	46.0	2.0	5.0	5.0	2015.000000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	2842.093023
3470	23.0	1.0	1.0	4.0	1938.000000	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	1570.000000
3471	41.0	2.0	1.0	6.0	1990.000000	0.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	2499.000000

Most frequently occurring

	area	room_num	floor	total_floor	year_built	dish_washer(zmywarka)	fridge(lodówka)	furniture(meble)	oven(piekarnik)	stove(kuchenka)	tv_set(telewizor)	washer(pralka)	balcony(balkon)	basement(piwnica)	elevator(winda)	internet	cable TV(telewizja kablowa)	air conditioning(klimatyzacja)	available for students(wynajmę również studentom)	terrace(taras)	build_type_Apartment_high_q(apartamentowiec)	build_type_Apartment_medium_q(blok)	build_type_Tenement(kamienica)	build_mat_Brick(cegła)	build_mat_Reinforced_concrete(żelbet)	build_mat_Silicate brick(silikat)	windows_Aluminum(aluminiowe)	windows_Plastic(plastikowe)	windows_Wooden(drewniane)	heating_Central(miejskie)	status_Ready(do_zamieszkania)	district_ Mokotów	district_ Praga-Północ	district_ Wola	district_ Śródmieście	district_ Żoliborz	gross_price	# duplicates
4	37.0	2.0	1.000000	4.0	1999.023256	1.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	1.0	2673.046512	3
0	26.0	1.0	6.000000	7.0	2019.000000	1.0	1.0	1.0	0.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	2200.000000	2
1	33.0	1.0	7.000000	15.0	2007.000000	0.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	2013.174419	2
2	35.0	2.0	3.686047	8.0	2013.000000	1.0	1.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	2500.000000	2
3	35.0	2.0	3.686047	8.0	2013.000000	1.0	1.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	2500.000000	2
5	40.0	1.0	6.000000	8.0	1987.790698	0.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	2200.000000	2
6	60.0	3.0	2.000000	5.0	2019.000000	1.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	0.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	3578.197674	2

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation